2019 EAMT Best Thesis Awardee

  • May 12, 2020 (updated on January 14, 2022)

Ten PhD theses defended in 2019 were received as candidates for the 2019 edition of the Anthony C Clarke Award – EAMT Best Thesis Award, and all ten were eligible. 36 reviewers and six EAMT Executive Committee members were recruited to examine and score the theses, considering how challenging the problem tackled in each thesis was, how relevant the results were for machine translation as a field, and what the strength of its impact in terms of scientific publications was. Two EAMT Executive Committee members also analysed all theses.

The year of 2019 was again a very good year for PhD theses in machine translation. The scores of the best theses were very close, which made it very hard to select a winner. A panel of five EAMT Executive Committee members (André Martins, Lucia Specia, Khalil Sima’an, Carolina Scarton, and Mikel L. Forcada) was assembled to process the reviews and select a winner.

The panel has then decided to grant the 2019 edition of the EAMT Best Thesis Award to Felix Stahlberg’s thesis “The Roles of Language Models and Hierarchical Models in Neural Sequence-to-Sequence Prediction” (University of Cambridge — now at Google), supervised by Bill Byrne and with Phil Woodland as advisor.

The awardee will receive a prize of €500, together with a suitably-inscribed certificate. In addition, Dr. Stahlberg has been invited to present a summary of his thesis at the 22nd Annual Conference of the European Association for Machine Translation (EAMT 2020: https://eamt2020.inesc-id.pt) which will take place in November (dates to be confirmed).

Mikel L. Forcada

EAMT President

Carolina Scarton

EAMT Secretary

Program committee

We would like to thank our reviewers that, despite the COVID-19 pandemic, still gave their time to review the theses and help us select the winner. Specially, Julia Ive, Iacer Calixto, José G. C. de Souza, and Jesús González Rubio that also acted as emergency reviewers.

  • Alon Lavie, Carnegie Mellon University
  • Andreas Maletti, Universität Leipzig
  • André Martins, Unbabel
  • Andy Way, Dublin City University
  • Antonio Toral, University of Groningen
  • Barry Haddow, University of Edinburgh
  • Celia Rico, Universidad Europea de Madrid
  • Christian Hardmeier, Uppsala University
  • Cristina España-Bonet, UdS and DFKI
  • Daniel Beck, University of Melbourne
  • Dimitar Shterionov, Dublin City University
  • Ekaterina Lapshinova-Koltunsk, Saarland University
  • Federico Gaspari, Dublin City University
  • Francisco Casacuberta, Universitat Politècnica de València
  • François Yvon, Université Paris-Sud
  • Frederic Blain, University of Sheffield
  • Iacer Calixto, University of Amsterdam
  • Jan Niehues, Maastricht University
  • Jesús González Rubio, WebInterpret
  • Joke Daems, Ghent University
  • José G. C. de Souza, Unbabel
  • Julia Ive, Imperial College London
  • Lieve Macken, Ghent University
  • Loïc Barrault, University of Sheffield
  • Longyue Wang, Tencent AI Lab
  • Lucia Specia, Imperial College London
  • Maja Popovic, Dublin City University
  • Marcello Federico, Amazon AI
  • Markus Freitag, Google AI
  • Matteo Negri, Fondazione Bruno Kessler
  • Mauro Cettolo, Fondazione Bruno Kessler
  • Miguel Domingo, Universitat Politècnica de València
  • Miquel Esplà, Universitat d’Alacant
  • Patrick Simianer, Lilt Inc.
  • Pavel Pecina, Charles University
  • Philipp Koehn, Johns Hopkins University
  • Qun Liu, Huawei Noah’s Ark Lab
  • Rico Sennrich, University of Zurich
  • Sharon O’Brien, Dublin City University
  • Sheila Castilho, Dublin City University
  • Vincent Vandeghinste, KU Leuven